Measuring Local-Area Racial Segregation for Medicare Hospital Admissions.

Importance: Considerable racial segregation exists in US hospitals that cannot be explained by where patients live. Approaches to measuring such segregation are limited. Objective: To measure how and where sorting of older Black patients to different hospitals occurs within the same health care market. Design, Setting, and Participants: This retrospective cross-sectional study used 2019 Medicare claims data linked to geographic data. Hospital zip code markets were based on driving time. The local hospital segregation (LHS) index was defined as the difference between the racial composition of a hospital's admissions and the racial composition of the hospital's market. Assessed admissions were among US Medicare fee-for-service enrollees aged 65 or older living in the 48 contiguous states with at least 1 hospitalization in 2019 at a hospital with at least 200 hospitalizations. Data were analyzed from November 2022 to January 2024. Exposure: Degree of residential segregation, ownership status, region, teaching hospital designation, and disproportionate share hospital status. Main Outcomes and Measures: The LHS index by hospital and a regional LHS index by hospital referral region. Results: In the sample of 1991 acute care hospitals, 4 870 252 patients (mean [SD] age, 77.7 [8.3] years; 2 822 006 [56.0%] female) were treated, including 11 435 American Indian or Alaska Native patients (0.2%), 129 376 Asian patients (2.6%), 597 564 Black patients (11.9%), 395 397 Hispanic patients (7.8), and 3 818 371 White patients (75.8%). In the sample, half of hospitalizations among Black patients occurred at 235 hospitals (11.8% of all hospitals); 878 hospitals (34.4%) exhibited a negative LHS score (ie, admitted fewer Black patients relative to their market area) while 1113 hospitals (45.0%) exhibited a positive LHS (ie, admitted more Black patients relative to their market area); of all hospitals, 79.4% exhibited racial admission patterns significantly different from their market. Hospital-level LHS was positively associated with government hospital status (coefficient, 0.24; 95% CI, 0.10 to 0.38), while New York, New York; Chicago, Illinois; and Detroit, Michigan, hospital referral regions exhibited the highest regional LHS measures, with hospital referral region LHS scores of 0.12, 0.16, and 0.21, respectively. Conclusions and Relevance: In this cross-sectional study, a novel measure of LHS was developed to quantify the extent to which hospitals were admitting a representative proportion of Black patients relative to their market areas. A better understanding of hospital choice within neighborhoods would help to reduce racial inequities in health outcomes.

Clinically informed machine learning elucidates the shape of hospice racial disparities within hospitals.

Racial disparities in hospice care are well documented for patients with cancer, but the existence, direction, and extent of disparity findings are contradictory across the literature. Current methods to identify racial disparities aggregate data to produce single-value quality measures that exclude important patient quality elements and, consequently, lack information to identify actionable equity improvement insights. Our goal was to develop an explainable machine learning approach that elucidates healthcare disparities and provides more actionable quality improvement information. We infused clinical information with engineering systems modeling and data science to develop a time-by-utilization profile per patient group at each hospital using US Medicare hospice utilization data for a cohort of patients with advanced (poor-prognosis) cancer that died April-December 2016. We calculated the difference between group profiles for people of color and white people to identify racial disparity signatures. Using machine learning, we clustered racial disparity signatures across hospitals and compared these clusters to classic quality measures and hospital characteristics. With 45,125 patients across 362 hospitals, we identified 7 clusters; 4 clusters (n = 190 hospitals) showed more hospice utilization by people of color than white people, 2 clusters (n = 106) showed more hospice utilization by white people than people of color, and 1 cluster (n = 66) showed no difference. Within-hospital racial disparity behaviors cannot be predicted from quality measures, showing how the true shape of disparities can be distorted through the lens of quality measures. This approach elucidates the shape of hospice racial disparities algorithmically from the same data used to calculate quality measures.

Development of My Decision/Mi Decisión, a web-based decision aid to support permanent contraception decision making.

Objective: To develop a patient-centered, web-based decision aid to support informed and value-concordant decision making among Medicaid enrollees considering tubal sterilization. Methods: We used the Ottawa Decision Support Framework and the International Patient Decision Aids Standards (IPDAS) to guide systematic development of our decision aid. We interviewed 15 obstetrician-gynecologists and 40 women, who had considered or were considering tubal sterilization. A Steering Committee-comprising healthcare providers, social scientists, reproductive health and justice advocates, and people with lived experience-provided feedback and direction. We developed English and Spanish prototypes, which were beta tested with 24 women. Results: The resulting web-based My Decision/Mi Decisión tool (English/Spanish) includes written and video information about tubal sterilization procedures; an interactive table of contraception options; values clarification exercises; reflection and deliberation; knowledge checks; and a summary report to share with one's provider. Users found the decision aid to be informative, engaging, easy to use, and helpful in informing contraception decision making. Conclusion: My Decision/Mi Decisión is a scalable tool that could be implemented widely to support informed decision making about tubal sterilization. Innovation: This is a novel and timely web-based decision tool for tubal sterilization, when demand for permanent contraception is rapidly increasing post-Dobbs. While designed for Medicaid enrollees, further investigation will explore more generalized use.

Evaluating Physician Emotion Regulation in Serious Illness Conversations Using Multimodal Assessment.

CONTEXT: Emotion regulation by the physician can influence the effectiveness of serious illness conversations. The feasibility of multimodal assessment of emotion regulation during these conversations is unknown. OBJECTIVES: To develop and assess an experimental framework for evaluating physician emotion regulation during serious illness conversations. METHODS: We developed and then assessed a multimodal assessment framework for physician emotion regulation using a cross-sectional, pilot study on physicians trained in the Serious Illness Conversation Guide (SICG) in a simulated, telehealth encounter. Development of the assessment framework included a literature review and subject matter expert consultations. Our predefined feasibility endpoints included: an enrollment rate of ≥60% of approached physicians, >90% completion rate of survey items, and <20% missing data from wearable heart rate sensors. To describe physician emotion regulation, we performed a thematic analysis of the conversation, its documentation, and physician interviews. RESULTS: Out of 12 physicians approached, 11 (92%) SICG-trained physicians enrolled in the study: five medical oncology and six palliative care physicians. All 11 completed the survey (100% completion rate). Two sensors (chest band, wrist sensor) had <20% missing data during study tasks. The forearm sensor had >20% missing data. The thematic analysis found that physicians': 1) overarching goal was to move beyond prognosis to reasonable hope; 2) tactically focused on establishing a trusting, supportive relationship; and 3) possessed incomplete awareness of their emotion regulation strategies. CONCLUSION: Our novel, multimodal assessment of physician emotion regulation was feasible in a simulated SICG encounter. Physicians exhibited an incomplete understanding of their emotion regulation strategies.

Development of dynamic health care delivery heatmaps for end-of-life cancer care: a cohort study.

OBJECTIVE: Measures of variation in end-of-life (EOL) care intensity across hospitals are typically summarised using unidimensional measures. These measures do not capture the full dimensionality of complex clinical care trajectories over time that are needed to inform quality improvement efforts. The objective is to develop a novel visual map of EOL care trajectories that illustrates multidimensional utilisation over time. SETTING: United States' National Cancer Institute or National Comprehensive Cancer Network (NCI/NCCN)-designated hospitals. PARTICIPANTS: We identified Medicare claims for fee-for-service beneficiaries with poor prognosis cancers who died between April and December 2016 and received the preponderance of treatment in the last 6 months of life at an NCI/NCCN-designated hospital. DESIGN: For each beneficiary, we transformed each Medicare claim into two elements to generate a two-dimensional individual-level heatmap. On the y-axis, each claim was classified into a categorical description of the service delivered by a healthcare resource. On the x-axis, the date for each claim was converted into the day number prior to death it occurred on. We then summed up individual-level heatmaps of patients attributed to each hospital to generate two-dimensional hospital-level heatmaps. We used four case studies to illustrate the feasibility of interpreting these heatmaps and to shed light on how they might be used to guide value-based, quality improvement initiatives. RESULTS: We identified nine distinct EOL care delivery patterns from hospital-level heatmaps based on signal intensity and patterns for inpatient, outpatient and home-based hospice services. We illustrate that in most cases, heatmaps illustrating patterns of multidimensional healthcare utilisation over time provide more information about care trajectories and highlight more heterogeneity than current unidimensional measures. CONCLUSIONS: This study illustrates the feasibility of representing multidimensional EOL utilisation over time as a heatmap. These heatmaps may provide potentially actionable insights into hospital-level care delivery patterns, and the approach may generalise to other serious illness populations.

Psychometric assessment of the consideRATE questions, a new measure of serious illness experience, with an online simulation study.

OBJECTIVE: To assess the psychometric properties of the consideRATE questions, a measure of serious illness experience. METHODS: We recruited people at least 50 years old via paid panels online, with US-Census-based quotas. We randomized participants to a patient experience story at two time points. Participants completed a series of measures, including the consideRATE questions. We assessed convergent (Pearson's correlation), discriminative (one-way ANOVA with Tukey's test for multiple comparisons) and divergent (Pearson's correlation) validity. We also assessed intra-rater reliability (intra-class correlation) and responsiveness to change (t-tests). RESULTS: We included 809 individuals in our analysis. We established convergent validity (r = 0.77; p < 0.001); discriminative validity (bad/neutral stories [mean diff=0.4; p < 0.001]; neutral/ good stories [mean diff=1.3; p < 0.001]) and moderate divergent validity (r = 0.57; p < 0.001). We established sensitivity to change in all stories (bad/good [mean diff=1.52; p < 0.001]; good/bad [mean diff= -1.68; p < 0.001]; neutral/bad [mean diff= -0.57; p < 0.001]; good/neutral [mean diff= -1.11; p < 0.001]; neutral/good [mean diff= 1.1; p < 0.001]) but one (bad/neutral [mean diff= 0.4; p < 0.07]). Intra-rater reliability was demonstrated between time points (r = 0.77; p < 0.001). CONCLUSIONS: the consideRATE questions were reliable and valid in a simulated online test. PRACTICE IMPLICATIONS: the consideRATE questions may be a practical way to measure serious illness experience and the effectiveness of interventions to improve it.

Outcomes after a Digital Behavior Change Intervention to Improve Trauma Triage: An Analysis of Medicare Claims.

BACKGROUND: Under-triage in trauma remains prevalent, in part because of decisions made by physicians at non-trauma centers. We developed two digital behavior change interventions to recalibrate physician heuristics (pattern recognition), and randomized 688 emergency medicine physicians to use the interventions or to a control. In this observational follow-up, we evaluated whether exposure to the interventions changed physician performance in practice. METHODS: We obtained 2016 - 2018 Medicare claims for severely injured patients, linked the names of trial participants to National Provider Identifiers (NPIs), and identified claims filed by trial participants for injured patients presenting to non-trauma centers in the year before and after their trial. The primary outcome measure was the triage status of severely injured patients. RESULTS: We linked 670 (97%) participants to NPIs, identified claims filed for severely injured patients by 520 (76%) participants, and claims filed at non-trauma centers by 228 (33%). Most participants were white (64%), male (67%), and had more than three years of experience (91%). Patients had a median Injury Severity Score of 16 (IQR 16 - 17), and primarily sustained neuro-trauma. After adjustment, patients treated by physicians randomized to the interventions experienced less under-triage in the year after the trial than before (41% versus 58% [-17%], P = 0.015); patients treated by physicians randomized to the control experienced no difference in under-triage (49% versus 56% [-7%], P = 0.35). The difference-in-the-difference was non-significant (10%, P = 0.18). CONCLUSIONS: It was feasible to track trial participants' performance in national claims. Sample size limitations constrained causal inference about the effect of the interventions.

US Ventilator Allocation and Patient Triage Policies in Anticipation of the COVID-19 Surge.

Before the predicted March 2020 surge of COVID-19, US healthcare organizations were charged with developing resource allocation policies. We assessed policy preparedness and substantive triage criteria within existing policies using a cross-sectional survey distributed to public health personnel and healthcare providers between March 23 and April 23, 2020. Personnel and providers from 68 organizations from 34 US states responded. While half of the organizations did not yet have formal allocation policies, all but 4 were in the process of developing policies. Using manual abstraction and natural language processing, we summarize the origins and features of the policies. Most policies included objective triage criteria, specified inapplicable criteria, separated triage and clinical decision making, detailed reassessment plans, offered an appeals process, and addressed palliative care. All but 1 policy referenced a sequential organ failure assessment score as a triage criterion, and 10 policies categorically excluded patients. Six policies were almost identical, tracing their origins to influenza planning. This sample of policies reflects organizational strategies of exemplar-based policy development and the use of objective criteria in triage decisions, either before or instead of clinical judgment, to support ethical distribution of resources. Future guidance is warranted on how to adapt policies across disease type, choose objective criteria, and specify processes that rely on clinical judgments.

Association Between Beta-Blockers and Mortality and Readmission in Older Patients with Heart Failure: an Instrumental Variable Analysis.

BACKGROUND: The demographics of heart failure are changing. The rate of growth of the "older" heart failure population, specifically those ≥ 75, has outpaced that of any other age group. These older patients were underrepresented in the early beta-blocker trials. There are several reasons, including a decreased potential for mortality benefit and increased risk of side effects, why the risk/benefit tradeoff may be different in this population. OBJECTIVE: We aimed to determine the association between receipt of a beta-blocker after heart failure discharge and early mortality and readmission rates among patients with heart failure and reduced ejection fraction (HFrEF), specifically patients aged 75+. DESIGN AND PARTICIPANTS: We used 100% Medicare Parts A and B and a random 40% sample of Part D to create a cohort of beneficiaries with ≥ 1 hospitalization for HFrEF between 2008 and 2016 to run an instrumental variable analysis. MAIN MEASURE: The primary measure was 90-day, all-cause mortality; the secondary measure was 90-day, all-cause readmission. KEY RESULTS: Using the two-stage least squared methodology, among all HFrEF patients, receipt of a beta-blocker within 30-day of discharge was associated with a - 4.35% (95% CI - 6.27 to - 2.42%, p < 0.001) decrease in 90-day mortality and a - 4.66% (95% CI - 7.40 to - 1.91%, p = 0.001) decrease in 90-day readmission rates. Even among patients ≥ 75 years old, receipt of a beta-blocker at discharge was also associated with a significant decrease in 90-day mortality, - 4.78% (95% CI - 7.19 to - 2.40%, p < 0.001) and 90-day readmissions, - 4.67% (95% CI - 7.89 to - 1.45%, p < 0.001). CONCLUSION: Patients aged ≥ 75 years who receive a beta-blocker after HFrEF hospitalization have significantly lower 90-day mortality and readmission rates. The magnitude of benefit does not appear to wane with age. Absent a strong contraindication, all patients with HFrEF should attempt beta-blocker therapy at/after hospital discharge, regardless of age.

Implementation and Impact of a Serious Illness Communication Training for Hematology-Oncology Fellows.

Effective communication between providers and patients with serious illness is critical to ensure that treatment is aligned with patient goals. We developed and tested an implementation strategy for incorporating the previously developed Serious Illness Conversation Guide (SICG), a clinician script, into hematology-oncology fellowship training at a single US academic medical center. Between December 2017 and April 2018, we trained 8 oncology fellows to use and document the SICG. The training included associated communication skills-such as handling emotion and headlining-over 7 didactic sessions. Implementation strategies included training 4 oncology faculty as coaches to re-enforce fellows' skills and an electronic medical record template to document the SICG. We assessed effectiveness using 4 approaches: (1) SICG template use among fellows in the 12 months following training, (2) fellow confidence pre- and post-intervention via survey, (3) performance in 2 simulated patient encounters, and (4) semi-structured interviews after 12 months. Fellows successfully implemented the SICG in simulated patient encounters, though only 2 of 6 fellows documented any SICG in the clinical practice. Most fellows reported greater confidence in their communication after training. Thematic analysis of interviews revealed the following: (1) positive training experience, (2) improved patient preference elicitation, (3) selected SICG components used in a single encounter, (4) prioritize other clinical duties, (5) importance of emotion handling skills, (6) no faculty coaching receive outside training. Despite acquisition of communication skills, promoting new clinical behaviors remains challenging. More work is needed to identify which implementation strategies are required in this learner population.

Opportunities and Challenges of Claims-Based Quality Assessment: The Case of Postdischarge ß-Blocker Treatment in Patients With Heart Failure With Reduced Ejection Fraction.

BACKGROUND: To combat the high cost and increasing burden of quality reporting, the Medicare Payment Advisory (MedPAC) has recommended using claims data wherever possible to measure clinical quality. In this article, we use a cohort of Medicare beneficiaries with heart failure with reduced ejection fraction and existing quality metrics to explore the impact of changes in quality metric methodology on measured quality performance, the association with patient outcomes, and hospital rankings. METHODS AND RESULTS: We used 100% Medicare Parts A and B and a random 40% sample of Part D from 2008 to 2015 to create (1) a cohort of 295 494 fee-for-service beneficiaries with ≥1 hospitalization for heart failure with reduced ejection fraction and (2) a cohort of 1079 hospitals with ≥11 heart failure with reduced ejection fraction admissions in 2014 and 2015. We used Part D data to calculate ß-blocker use after discharge and ß-blocker use over time. We then varied the quality metric methodologies to explore the impact on measured performance. We then used multivariable time-to-event analyses to explore the impact of metric methodology on the association between quality performance and patient outcomes and Kendall's Tau to describe impact of quality metric methodology on hospital rankings. We found that quality metric methodology had a significant impact on measured quality performance. The association between quality performance and readmissions was sensitive to changes in methodology but the association with 1-year mortality was not. Changes in quality metric methodology also had a substantial impact on hospital quality rankings. CONCLUSIONS: This article highlights how small changes in quality metric methodology can have a significant impact on measured quality performance, the association between quality performance and utilization-based outcomes, and hospital rankings. These findings highlight the need for standardized quality metric methodologies, better case-mix adjustment and cast further doubt on the use of utilization-based outcomes as quality metrics in chronic diseases.

End-of-life quality metrics among medicare decedents at minority-serving cancer centers: A retrospective study.

BACKGROUND: We calculated the performance of National Cancer Institute (NCI)/National Comprehensive Cancer Network (NCCN) cancer centers' end-of-life (EOL) quality metrics among minority and white decedents to explore center-attributable sources of EOL disparities. METHODS: We conducted a retrospective cohort study of Medicare beneficiaries with poor-prognosis cancers who died between April 1, 2016 and December 31, 2016 and had any inpatient services in the last 6 months of life. We attributed patients' EOL treatment to the center at which they received the preponderance of EOL inpatient services and calculated eight risk-adjusted metrics of EOL quality (hospice admission ≤3 days before death; chemotherapy last 14 days of life; ≥2 emergency department (ED) visits; intensive care unit (ICU) admission; or life-sustaining treatment last 30 days; hospice referral; palliative care; advance care planning last 6 months). We compared performance between patients across and within centers. RESULTS: Among 126,434 patients, 10,119 received treatment at one of 54 NCI/NCCN centers. In aggregate, performance was worse among minorities for ED visits (10.3% vs 7.4%, P < .01), ICU admissions (32.9% vs 30.4%, P = .03), no hospice referral (39.5% vs 37.0%, P = .03), and life-sustaining treatment (19.4% vs 16.2%, P < .01). Despite high within-center correlation for minority and white metrics (0.61-0.79; P < .01), five metrics demonstrated worse performance as the concentration of minorities increased: ED visits (P = .03), ICU admission (P < .01), no hospice referral (P < .01), and life-sustaining treatments (P < .01). CONCLUSION: EOL quality metrics vary across NCI/NCCN centers. Within center, care was similar for minority and white patients. Minority-serving centers had worse performance on many metrics.

The Development and Validation of Prostate Cancer-specific Physician-Hospital Networks.

OBJECTIVE: To develop prostate cancer-specific physician-hospital networks to define hospital-based units that more accurately group hospitals, providers, and the patients they serve. METHODS: Using Surveillance, Epidemiology, and End Results-Medicare, we identified men diagnosed with localized prostate cancer between 2007 and 2011. We created physician-hospital networks by assigning each patient to a physician and each physician to a hospital based on treatment patterns. We assessed content validity by examining characteristics of hospitals anchoring the physician-hospital networks and of the patients associated with these hospitals. RESULTS: We identified 42,963 patients associated with 344 physician-hospital networks. Networks anchored by a teaching hospital (compared to a nonteaching hospital) had higher median numbers of prostate cancer patients (117 [interquartile range {71-189} vs 82 {50-126}]) and treating physicians (7 [4-11] vs 4 [3-6]) (both P <0.001). On average, patients traveled farther to networks anchored by a teaching hospital (49 miles [standard deviation] [207] vs 41 [183]; P <.001). Hospitals known as high-volume centers for robotic prostatectomies, proton-beam therapy, and active surveillance had network rates for these procedures well above the mean. Hospitals known as safety net providers served higher proportions of minorities. CONCLUSION: We empirically developed prostate-cancer specific physician-hospital networks that exhibit content validity and are relevant from a clinical and policy perspective. They have the potential to become targets for policy interventions focused on improving the delivery of prostate cancer care.

Association of Practitioner Interfacility Triage Performance With Outcomes for Severely Injured Patients With Fee-for-Service Medicare Insurance.

Importance: Despite evidence that treatment of severely injured patients at trauma centers is associated with reduced mortality, nearly half of all such patients are treated at nontrauma centers (undertriaged). Little is known about whether interfacility undertriage occurs because of practitioner decision-making or institutional and regional factors. Objectives: To assess the associations between variation in triage practitioners at nontrauma centers and between practitioner-level variation and patient outcomes after injury. Design, Setting, and Participants: This retrospective cohort study used Medicare claims data from severely injured patients presenting to nontrauma centers and the practitioners who evaluated them in the emergency department from January 1, 2010, to October 15, 2015. Data analysis was performed from January 15, 2018, to March 21, 2019. Main Outcomes and Measures: Proportion of variation in undertriage associated with practitioners, practitioner rates of undertriage, practitioner characteristics associated with undertriage, and 30-day case-fatality rate. Results: A total of 124 008 severely injured patients (mean [SD] age, 81 [8.4] years; 67 253 [54.2%] female) and the 25 376 practitioners (5564 [21.9%] female) who evaluated the patients in the emergency department of nontrauma centers were included in the study. Undertriage occurred among 85 403 patients (68.9%), with 40.6% of total variation associated with practitioners, 37.8% with hospitals, and 6.7% with regions. Compared with physicians with National Provider Identification (NPI) enumeration before 2007, those with an NPI enumerated between 2007 and 2010 had an undertriage risk ratio (RR) of 0.98 (95% CI, 0.97-0.99), and those with an NPI enumerated after 2010 had an undertriage RR of 0.96 (95% CI, 0.94-0.99). Hospitals with neurosurgeons had an undertriage RR of 1.51 (95% CI, 1.45-1.57) compared with those that did not; hospitals with spine surgeons had an undertriage RR of 1.10 (95% CI, 1.06-1.13); hospitals with general surgeons had an undertriage RR of 1.13 (95% CI, 1.09-1.17). Compared with practitioners who undertriaged 25% or less of patients, a statistically significant increase was found in the odds of death for patients treated by practitioners with a triage rate of less than 25% to 50% (odds ratio [OR], 1.08; 95% CI, 1.05-1.20) and less than 50% to 75% undertriage (OR, 1.12; 95% CI, 1.09-1.26) but not undertriage at greater than 75% (OR, 1.03, 95% CI, 1.00-1.18). In sensitivity analyses to adjust for unmeasured confounding, the association between triage practices and the case fatality rate became monotonic; compared with patients treated by practitioners with an undertriage rate of 25% or less, the odds of case fatality were 1.13 (95% CI, 1.05-1.21; P = .001) among patients treated by practitioners with undertriage rates less than 25% to 50%, 1.22 (95% CI, 1.13-1.32; P < .001) for patients treated by practitioners with undertriage rates less than 50% to 75%, and 1.20 (95% CI, 1.10-1.30; P < .001) for patients treated by practitioners with undertriage rates greater than 75%. Conclusions and Relevance: The findings suggest that individual practitioner practices are an important source of variation in triage and represent a potential locus of intervention to reduce preventable deaths after injury.

Change in Functional Status After Prostate Cancer Treatment Among Medicare Advantage Beneficiaries.

OBJECTIVE: To examine the relationship between treatment and subsequent functional status among prostate cancer patients. METHODS: Using Surveillance, Epidemiology, and End Results-Medicare Health Outcomes Survey data, we identified men 65 years or older diagnosed with prostate cancer between 1998 and 2009 (follow-up through 2010) who were treated with conservative management, surgery, or radiation. Our primary outcome was functional status as measured by activities of daily living. Secondary outcomes included physical component summary and mental component summary scores, which are both calculated from the Short Form 36 (SF-36) and the Veterans RAND 12-item health survey (VR-12) questionnaires. We included patients who completed 2 surveys and performed propensity score analyses to match patients 1:5 with noncancer controls. We used generalized linear mixed effects models, accounting for clustering due to insurance plan. RESULTS: We identified 408 patients of whom 143 (35%) underwent conservative management, 59 (14%) underwent surgery, and 206 (51%) underwent radiation. Among conservative management and radiation patients, changes in functional status mirrored that of their noncancer controls (all P > .05). Among surgery patients, changes in activities of daily living scores were not significant, but physical component summary (mean difference = 4.5, P < .001) and mental component summary (mean difference = 3.3, P = .01) scores declined slightly more than for their noncancer peers. CONCLUSION: Surgery patients had a slight decline in their general functional status whereas conservative management and radiation patients had no differences in functional status compared with their noncancer peers. Although the functional status of surgery patients declined more than that of their noncancer peers, this difference may not be clinically significant.

Does Preexisting Practice Modify How Video Games Recalibrate Physician Heuristics in Trauma Triage?

BACKGROUND: A majority of severely injured patients fail to receive care at trauma centers (undertriage), in part, because of physician judgment. We previously developed two educational video games that reduced physicians' undertriage compared with control in two clinical trials. In this secondary analysis, we investigated heterogeneity of treatment effect of the interventions by assessing physicians' preexisting practice patterns in claims data. We hypothesized that physicians with high preexisting undertriage would benefit most from game-based training. METHODS: Using Medicare claims records from 2010 to 2015, we measured physicians' preexisting triage practices before their participation in one of two trials conducted in 2016 and 2017. We categorized physicians as having received game-based training versus control and noted their postintervention simulation triage performance in the trials. We used multivariable linear regression models to assess the heterogeneity of game-based training effect among physicians with high and low preexisting undertriage. RESULTS: Of the 394 eligible physicians from our trials, we identified 275 (70%) with claims for Medicare fee-for-service beneficiaries suffering severe injury between 2010 and 2015. On average, the physicians were 44 y old (SD 8.4) with 12 y (SD 8.2) of experience. We found significant interaction between preexisting practice and intervention efficacy (P = 0.04). Physicians with high undertriage before enrollment improved significantly with game-based training compared with the control (46% versus 63%, P < 0.001). Those with low preexisting undertriage did not (58% versus 56%, P = 0.76). CONCLUSIONS: Using claims-based data, we found heterogeneity of treatment effect of interventions designed to recalibrate physician heuristics. Physicians with high preexisting undertriage benefited most from game-based training.

Use of Advance Care Planning Billing Codes for Hospitalized Older Adults at High Risk of Dying: A National Observational Study.

We analyzed advance care planning (ACP) billing for adults aged 65 years or above and who were managed by a large national physician practice that employs acute care providers in hospital medicine, emergency medicine and critical care between January 1, 2017 and March 31, 2017. Prompting hospitalists to answer the validated "surprise question" (SQ; "Would you be surprised if the patient died in the next year?") for inpatient admissions served to prime hospitalists and triggered an icon next to the patient's name. Among 113,621 hospital-based encounters, only 6,146 (5.4%) involved a billed ACP conversation: 8.3% among SQ-prompted who answered "no" and 4.1% SQ-prompted who answered "yes" (for non-SQ prompted cases, the fraction was 3.5%; P < .0001). ACP conversations were associated with a comfort-focused care trajectory. Low ACP rates among even those with high hospitalist-predicted mortality risk underscore the need for quality improvement interventions to increase hospital-based ACP.

Value Awareness: A New Goal for End-of-life Decision Making.

The principal policy tool for respecting the preferences of patients facing serious illnesses that can prompt decisions regarding end-of-life care is the advance directive (AD) for health care. AD policies, decision aids for facilitating ADs, and clinical processes for interpreting ADs all treat patients as rational actors who will make appropriate choices, if provided relevant information. We review barriers to following this model, leading us to propose replacing the goal of rational choice with that of value awareness, enabling patients (and, where appropriate, their surrogates) to be as rational as they can and want to be when making these fateful choices. We propose approaches, and supporting research, suited to individuals' cognitive, affective, and social circumstances, resources, and desires.

The Paradox of End-of-Life Hospital Treatment Intensity among Black Patients: A Retrospective Cohort Study.

OBJECTIVE: Black patients are more likely than white patients to die in the hospital with intensive care and life-sustaining treatments and less likely to use hospice. Regional concentration of high end-of-life (EOL) treatment intensity practice patterns may disproportionately affect black patients. We calculated and compared race-specific hospital-level EOL treatment intensity in Pennsylvania. METHODS: We conducted a retrospective cohort analysis of Pennsylvania acute care hospital admissions, 2001-2007, among black and white admissions ≥21 years old at high probability of dying (HPD) (≥15% predicted probability of dying at admission). We calculated hospitals' race-specific observed, expected, and Bayes' shrunken observed-to-expected ratios of intensive care unit (ICU) admission, ICU length of stay (LOS), intubation/mechanical ventilation, hemodialysis, tracheostomy, and gastrostomy among HPD admissions; and an empirically weighted EOL treatment intensity index summing these ratios. RESULTS: There were 35,609 black HPD admissions (27,576 unique patients) and 311,896 white HPD admissions (252,662 unique patients) to 182 hospitals. Among 95 hospitals with ≥30 black HPD admissions, 80% of black admissions were concentrated in 29 hospitals, where black-specific observed and expected EOL measures were usually higher than white-specific measures (p < 0.001 for all but 5/24 measures). Hospitals' black-specific and white-specific observed-to-expected ratios of ICU and life-sustaining treatment (LST) (rho 0.52-0.90) and EOL index (rho = 0.92) were highly correlated. However, black-specific observed-to-expected ratios and overall EOL intensity index were consistently lower than white-specific ratios (p < 0.001 for all except hemodialysis). CONCLUSIONS: In Pennsylvania, black-serving hospitals have higher standardized EOL treatment intensity than nonblack-serving hospitals, contributing to black patients' relatively higher use of intensive treatment. However, conditional on being admitted to the same high-intensity hospital and after risk adjustment, blacks are less intensively treated than whites.